In this paper we present a novel strategy, DragPushing, for improving the performance of text classifiers. The strategy is generic and takes advantage of training errors to succes...
Songbo Tan, Xueqi Cheng, Moustafa Ghanem, Bin Wang...
The nature of the internet as a non-peer-reviewed (and more generally largely unregulated) publication medium has allowed wide-spread promotion of inaccurate and unproven medical ...
We investigate the problem of learning document classifiers in a multilingual setting, from collections where labels are only partially available. We address this problem in the ...
The world wide web has a wealth of information that is related to almost any text classification task. This paper presents a method for mining the web to improve text classificati...
This paper describes the retrieval approach proposed by the SIG/EVI group of the IRIT research centre in INEX’2004 evaluation. The approach uses a voting method coupled with some...